






"""simple docstring"""





import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch

import multiprocess
import numpy as np
import pytest

from datasets.utils.py_utils import (
    NestedDataStructure,
    asdict,
    iflatmap_unordered,
    map_nested,
    temp_seed,
    temporary_assignment,
    zip_dict,
)

from .utils import require_tf, require_torch







def 	lowerCamelCase__			(				_lowerCamelCase			:						Any					) ->							Tuple:  # picklable for multiprocessing
  return x.sum()







def 	lowerCamelCase__			(				_lowerCamelCase			:						str					) ->							List[str]:  # picklable for multiprocessing
  return i + 1






@dataclass
class 	a		:
    SCREAMING_SNAKE_CASE		:	int
    SCREAMING_SNAKE_CASE		:	str






class 	a		(   __snake_case						):






    def   UpperCamelCase			(			self	:				Union[str, Any]   )	->						int:
      lowerCamelCase_       	=		{}
      lowerCamelCase_       	=		[]
      lowerCamelCase_       	=		1
      lowerCamelCase_       	=		[1, 2]
      lowerCamelCase_       	=		{'a': 1, 'b': 2}
      lowerCamelCase_       	=		{'a': [1, 2], 'b': [3, 4]}
      lowerCamelCase_       	=		{'a': {'1': 1}, 'b': 2}
      lowerCamelCase_       	=		{'a': 1, 'b': 2, 'c': 3, 'd': 4}
      lowerCamelCase_       	=		{}
      lowerCamelCase_       	=		[]
      lowerCamelCase_       	=		2
      lowerCamelCase_       	=		[2, 3]
      lowerCamelCase_       	=		{'a': 2, 'b': 3}
      lowerCamelCase_       	=		{'a': [2, 3], 'b': [4, 5]}
      lowerCamelCase_       	=		{'a': {'1': 2}, 'b': 3}
      lowerCamelCase_       	=		{'a': 2, 'b': 3, 'c': 4, 'd': 5}
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		2
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )

      lowerCamelCase_       	=		{'a': np.eye(2   ), 'b': np.zeros(3   ), 'c': np.ones(2   )}
      lowerCamelCase_       	=		{'a': 2, 'b': 0, 'c': 2}
      lowerCamelCase_       	=		{
          'a': np.eye(2   ).astype(__SCREAMING_SNAKE_CASE   ),
          'b': np.zeros(3   ).astype(__SCREAMING_SNAKE_CASE   ),
          'c': np.ones(2   ).astype(__SCREAMING_SNAKE_CASE   ),
      }
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		map_numpy=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(
          {k: v.tolist() for k, v in map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		map_numpy=__SCREAMING_SNAKE_CASE   ).items()}			,		{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}			,		)
      self.assertEqual(map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		map_numpy=__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )			,		__SCREAMING_SNAKE_CASE   )
      self.assertEqual(
          {k: v.tolist() for k, v in map_nested(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		map_numpy=__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   ).items()}			,		{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}			,		)
      with self.assertRaises(__SCREAMING_SNAKE_CASE   ):  # can't pickle a local lambda
        map_nested(lambda __SCREAMING_SNAKE_CASE   : x + 1			,		__SCREAMING_SNAKE_CASE			,		num_proc=__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				str   )	->						Optional[int]:
      lowerCamelCase_       	=		{'a': 1, 'b': 2}
      lowerCamelCase_       	=		{'a': 3, 'b': 4}
      lowerCamelCase_       	=		{'a': 5, 'b': 6}
      lowerCamelCase_       	=		sorted([('a', (1, 3, 5)), ('b', (2, 4, 6))]   )
      self.assertEqual(sorted(zip_dict(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )   )			,		__SCREAMING_SNAKE_CASE   )






    def   UpperCamelCase			(			self	:				List[str]   )	->						List[Any]:






      class 	a		:
          SCREAMING_SNAKE_CASE		:	Tuple		=					"""bar"""
      lowerCamelCase_       	=		Foo()
      self.assertEqual(foo.my_attr			,		'bar'   )
      with temporary_assignment(__SCREAMING_SNAKE_CASE			,		'my_attr'			,		'BAR'   ):
        self.assertEqual(foo.my_attr			,		'BAR'   )
      self.assertEqual(foo.my_attr			,		'bar'   )







@pytest.mark.parametrize(
    'iterable_length, num_proc, expected_num_proc'						,							[
        (1, None, 1),
        (1, 1, 1),
        (2, None, 1),
        (2, 1, 1),
        (2, 2, 1),
        (2, 3, 1),
        (3, 2, 1),
        (16, 16, 16),
        (16, 17, 16),
        (17, 16, 16),
    ]						,							)
def 	lowerCamelCase__			(				_lowerCamelCase			:						Union[str, Any]						,							_lowerCamelCase			:						Optional[Any]						,							_lowerCamelCase			:						List[Any]					) ->							Dict:
  with patch('datasets.utils.py_utils._single_map_nested'					) as mock_single_map_nested, patch(
      'datasets.parallel.parallel.Pool'					) as mock_multiprocessing_pool:
    lowerCamelCase_       	=		{F'''{i}''': i for i in range(_lowerCamelCase					)}
    lowerCamelCase_       	=		map_nested(lambda _lowerCamelCase					: x + 10						,							_lowerCamelCase						,							num_proc=_lowerCamelCase						,							parallel_min_length=16					)
    if expected_num_proc == 1:
      assert mock_single_map_nested.called
      assert not mock_multiprocessing_pool.called
    else:
      assert not mock_single_map_nested.called
      assert mock_multiprocessing_pool.called
      assert mock_multiprocessing_pool.call_args[0][0] == expected_num_proc






class 	a		(   __snake_case						):






    @require_tf
    def   UpperCamelCase			(			self	:				Dict   )	->						List[str]:
      import tensorflow as tf
      from tensorflow.keras import layers

      lowerCamelCase_       	=		layers.Dense(2   )

      def gen_random_output():
        lowerCamelCase_       	=		tf.random.uniform((1, 3)   )
        return model(__SCREAMING_SNAKE_CASE   ).numpy()

      with temp_seed(42			,		set_tensorflow=__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		gen_random_output()
      with temp_seed(42			,		set_tensorflow=__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		gen_random_output()
      lowerCamelCase_       	=		gen_random_output()

      np.testing.assert_equal(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )
      self.assertGreater(np.abs(outa - outa   ).sum()			,		0   )






    @require_torch
    def   UpperCamelCase			(			self	:				Any   )	->						Optional[Any]:
      import torch

      def gen_random_output():
        lowerCamelCase_       	=		torch.nn.Linear(3			,		2   )
        lowerCamelCase_       	=		torch.rand(1			,		3   )
        return model(__SCREAMING_SNAKE_CASE   ).detach().numpy()

      with temp_seed(42			,		set_pytorch=__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		gen_random_output()
      with temp_seed(42			,		set_pytorch=__SCREAMING_SNAKE_CASE   ):
        lowerCamelCase_       	=		gen_random_output()
      lowerCamelCase_       	=		gen_random_output()

      np.testing.assert_equal(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )
      self.assertGreater(np.abs(outa - outa   ).sum()			,		0   )






    def   UpperCamelCase			(			self	:				Optional[Any]   )	->						Union[str, Any]:
      def gen_random_output():
        return np.random.rand(1			,		3   )

      with temp_seed(42   ):
        lowerCamelCase_       	=		gen_random_output()
      with temp_seed(42   ):
        lowerCamelCase_       	=		gen_random_output()
      lowerCamelCase_       	=		gen_random_output()

      np.testing.assert_equal(__SCREAMING_SNAKE_CASE			,		__SCREAMING_SNAKE_CASE   )
      self.assertGreater(np.abs(outa - outa   ).sum()			,		0   )







@pytest.mark.parametrize('input_data'						,							[{}]					)
def 	lowerCamelCase__			(				_lowerCamelCase			:						Tuple					) ->							Union[str, Any]:
  lowerCamelCase_       	=		NestedDataStructure(_lowerCamelCase					).data
  assert output_data == input_data







@pytest.mark.parametrize(
    'data, expected_output'						,							[
        ({}, []),
        ([], []),
        ('foo', ['foo']),
        (['foo', 'bar'], ['foo', 'bar']),
        ([['foo', 'bar']], ['foo', 'bar']),
        ([[['foo'], ['bar']]], ['foo', 'bar']),
        ([[['foo'], 'bar']], ['foo', 'bar']),
        ({'a': 1, 'b': 2}, [1, 2]),
        ({'a': [1, 2], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[1, 2]], 'b': [[3, 4]]}, [1, 2, 3, 4]),
        ({'a': [[1, 2]], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [[[3], [4]]]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [[3, 4]]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [3, [4]]}, [1, 2, 3, 4]),
        ({'a': {'1': 1}, 'b': 2}, [1, 2]),
        ({'a': {'1': [1]}, 'b': 2}, [1, 2]),
        ({'a': {'1': [1]}, 'b': [2]}, [1, 2]),
    ]						,							)
def 	lowerCamelCase__			(				_lowerCamelCase			:						Union[str, Any]						,							_lowerCamelCase			:						Any					) ->							List[Any]:
  lowerCamelCase_       	=		NestedDataStructure(_lowerCamelCase					).flatten()
  assert output == expected_output







def 	lowerCamelCase__			(				) ->							Optional[Any]:
  lowerCamelCase_       	=		A(x=1						,							y='foobar'					)
  lowerCamelCase_       	=		{'x': 1, 'y': 'foobar'}
  assert asdict(_lowerCamelCase					) == expected_output

  lowerCamelCase_       	=		{'a': {'b': A(x=10						,							y='foo'					)}, 'c': [A(x=20						,							y='bar'					)]}
  lowerCamelCase_       	=		{'a': {'b': {'x': 10, 'y': 'foo'}}, 'c': [{'x': 20, 'y': 'bar'}]}
  assert asdict(_lowerCamelCase					) == expected_output

  with pytest.raises(_lowerCamelCase					):
    asdict([1, A(x=10						,							y='foo'					)]					)







def 	lowerCamelCase__			(				_lowerCamelCase			:						str					) ->							Optional[int]:
  return text.split()







def 	lowerCamelCase__			(				_lowerCamelCase			:						Dict					) ->							Any:
  yield (time.time(), content)
  time.sleep(2					)
  yield (time.time(), content)







def 	lowerCamelCase__			(				) ->							Dict:
  with Pool(2					) as pool:
    lowerCamelCase_       	=		list(iflatmap_unordered(_lowerCamelCase						,							_split_text						,							kwargs_iterable=[{'text': 'hello there'}] * 10					)					)
    assert out.count('hello'					) == 10
    assert out.count('there'					) == 10
    assert len(_lowerCamelCase					) == 20

  # check multiprocess from pathos (uses dill for pickling)
  with multiprocess.Pool(2					) as pool:
    lowerCamelCase_       	=		list(iflatmap_unordered(_lowerCamelCase						,							_split_text						,							kwargs_iterable=[{'text': 'hello there'}] * 10					)					)
    assert out.count('hello'					) == 10
    assert out.count('there'					) == 10
    assert len(_lowerCamelCase					) == 20

  # check that we get items as fast as possible
  with Pool(2					) as pool:
    lowerCamelCase_       	=		[]
    for yield_time, content in iflatmap_unordered(
        _lowerCamelCase						,							_aseconds_generator_of_aitems_with_timing						,							kwargs_iterable=[{'content': 'a'}, {'content': 'b'}]					):
      assert yield_time < time.time() + 0.1, "we should each item directly after it was yielded"
      out.append(_lowerCamelCase					)
    assert out.count('a'					) == 2
    assert out.count('b'					) == 2
    assert len(_lowerCamelCase					) == 4












"""simple docstring"""





from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403







def 	lowerCamelCase__			(				_lowerCamelCase			:						str						,							_lowerCamelCase			:						complex						,							_lowerCamelCase			:						str = "x"						,							_lowerCamelCase			:						float = 10**-10						,							_lowerCamelCase			:						int = 1						,							) ->							complex:
  lowerCamelCase_       	=		symbols(_lowerCamelCase					)
  lowerCamelCase_       	=		lambdify(_lowerCamelCase						,							_lowerCamelCase					)
  lowerCamelCase_       	=		lambdify(_lowerCamelCase						,							diff(_lowerCamelCase						,							_lowerCamelCase					)					)

  lowerCamelCase_       	=		starting_point

  while True:
    if diff_function(_lowerCamelCase					) != 0:
      lowerCamelCase_       	=		prev_guess - multiplicity * func(_lowerCamelCase					) / diff_function(
          _lowerCamelCase					)
    else:
      raise ZeroDivisionError('Could not find root'					) from None

    # Precision is checked by comparing the difference of consecutive guesses
    if abs(next_guess - prev_guess					) < precision:
      return next_guess

    lowerCamelCase_       	=		next_guess


# Let's Execute
if __name__ == "__main__":
  # Find root of trigonometric function
  # Find value of pi
  print(F'''The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}''')

  # Find root of polynomial
  # Find fourth Root of 5
  print(F'''The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5j)}''')

  # Find value of e
  print(
      '''The root of log(y) - 1 = 0 is ''',
      F'''{newton_raphson('log(y) - 1', 2, variable='y')}''',
  )

  # Exponential Roots
  print(
      '''The root of exp(x) - 1 = 0 is''',
      F'''{newton_raphson('exp(x) - 1', 10, precision=0.005)}''',
  )

  # Find root of cos(x)
  print(F'''The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}''')




